{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:26:04.342468Z",
     "start_time": "2018-02-18T20:26:03.812273Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import sys\n",
    "sys.path.insert(0, '../src/easyesn/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:26:10.582740Z",
     "start_time": "2018-02-18T20:26:04.440365Z"
    }
   },
   "outputs": [],
   "source": [
    "from easyesn import PredictionESN, BaseESN\n",
    "from easyesn import helper as hlp\n",
    "from easyesn.optimizers import GradientOptimizer\n",
    "import matplotlib.pyplot as plt\n",
    "import easyesn\n",
    "\n",
    "np.random.seed(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:54:38.603607Z",
     "start_time": "2018-02-18T20:54:38.556071Z"
    }
   },
   "outputs": [],
   "source": [
    "#generate train/test data\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\"\"\"\n",
    "inputLength = 1000\n",
    "trainingLength = int(inputLength*0.7)\n",
    "data = np.linspace(0, 10*np.pi, inputLength).reshape(-1,1)\n",
    "inputData = np.sin(data)\n",
    "outputData = np.cos(data)\n",
    "\"\"\"\n",
    "\n",
    "inputData = np.loadtxt(\"ShinrikiX.txt\").reshape((-1, 1))\n",
    "outputData = inputData[84:]\n",
    "inputData = inputData[:-84]\n",
    "\n",
    "\n",
    "inputLength = len(inputData)\n",
    "trainingLength = int(inputLength*0.7)\n",
    "\n",
    "inputDataTraining = inputData[:trainingLength]\n",
    "inputDataValidation = inputData[trainingLength:]\n",
    "\n",
    "outputDataTraining = outputData[:trainingLength]\n",
    "outputDataValidation = outputData[trainingLength:]\n",
    "\n",
    "transientTime = 100\n",
    "splitLength = 1000\n",
    "overlapLength = 100\n",
    "splitNumber = int(np.ceil(trainingLength / splitLength))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:54:22.676390Z",
     "start_time": "2018-02-18T20:54:22.393105Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "reservoirs = []\n",
    "reservoirs.append(PredictionESN(n_input=1, n_output=1, n_reservoir=50, leakingRate=0.2, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False))\n",
    "\n",
    "for i in range(splitNumber-1):\n",
    "    reservoirs.append(PredictionESN(n_input=1, n_output=1, n_reservoir=50, leakingRate=0.2, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False))\n",
    "    reservoirs[-1]._W = reservoirs[0]._W\n",
    "    reservoirs[-1]._WInput = reservoirs[0]._WInput\n",
    "    \n",
    "states = np.empty((50 + 1 + 1, trainingLength))\n",
    "for i in range(splitNumber):\n",
    "    reservoirs[i].resetState()\n",
    "    dataEnd = min((i+1) * splitLength, trainingLength)\n",
    "    dataStart = max(0, i*splitLength - overlapLength)\n",
    "    data = inputDataTraining[dataStart:dataEnd]\n",
    "    stat = reservoirs[i].propagate(data)\n",
    "    states[:, i*splitLength:dataEnd] = stat[:, 0 if i==0 else overlapLength:]\n",
    "\n",
    "Y_target = outputDataTraining.T[:, transientTime:]\n",
    "\n",
    "states = states[:, transientTime:]\n",
    "\n",
    "X_T = states.T\n",
    "_WOut = np.dot(np.dot(Y_target, X_T), np.linalg.inv(np.dot(states,X_T) + reservoirs[0]._regressionParameters[0]*np.identity(1+1+50)))\n",
    "\n",
    "reservoirs[-1]._WOut = _WOut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:54:22.783102Z",
     "start_time": "2018-02-18T20:54:22.716482Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "prediction = reservoirs[-1].predict(inputDataValidation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:54:23.426788Z",
     "start_time": "2018-02-18T20:54:23.156020Z"
    }
   },
   "outputs": [
    {
     "data": {
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djqsGH25LPaJuRH0VNU4xI+ppqi5vJRiQSMlKILsomZqDjoE2KSZKzy3k1j8tpa6tHICC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rbz5o8nmYyPEFLLC0UJSuUpTrW9jNXmOmZaTbCvH34dXbbkF6ef4fn9f0lJEdwxcJev5zBjp4lU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\nwX61aClD7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      "text/plain": [
       "<matplotlib.figure.Figure at 0x24da67c99b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RlIOKojyixTE9Yf2RCq79cD3/W+9dwozZLGhulU/0wuomktuShyyk2cj8pGE3WONoG7Mr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\nMD4jnkvGpfLJmmy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5N5/oP3nmscLh32DRn+H2tRAWC4mZ8EgOhPqxRkpVDoQnQnA4/PkP\niNTIO3eErfO1cyF8dT3csR6SPO8K5i+6p2H/6gYoOwB3+tEDqMySr37THH48PiPemrLsK5P7JzK5\nfyLUl8Oun6VHGOE+cSomPIhLJ6TxxbocDDqFebdO8iiulxQZQktbGKdbeewACf3lfx/YJ3/M/uDS\nTwAYVH20YNZ51XNgcSuc9bKqQwzoEcmjZw5mwaZ8Hjx9kNOCUscVIy6W4oDETPn/Op1/jbrJKOPr\n0x5rm8339N9Y7ek9Fk7/u8O4flfS/UIxAONvgFP+4t8x9nwHn10ADX7oeGJshBf7SzmdLeUHYP61\nULBF9aGeOGsIj80ezP9uOdFjo2HrpScfg1p1h+Ssg+/uldNf8J9Rt8E23NY7rFXG+D3glqn9+fm+\nqS6LVx1X6IMgZYT9gumhZfDjw/4ZTwg4720YdIb8/6ocWPosVPrWStIpC2+BXYvkv+My5CK7P2cI\nXtA9DfuAGdIr8CfDLoQ/LYKdC2CLxvE6c6tcWIprV8QrZaScRqar1+mHBxu4ZWp/r2YPthUy+yUe\nG4vRbqk4DLu+BkObsa0vh69uhAO/ajtO2QF492Q4shJFUXhwViaj0mJJuPBFuOg/2o51vLHxI/kA\ntqV4N+yYL+PtWmMIliqcnlI6TFMN/PEaFPuhLYSpFfI3Q41Nk7imGqhw31ylM1E6q7mqLePHjxcb\nN270/gBmkwyThMZChH+q+ln5aDaEx0vp1nFGS6uZzCd+BGDXM6c7LU96zCEEWBYfW1vg7Qkw9S8w\n5irtxig7KBVKUx9yqHoI4ASzGf7eU2rJZ/3N/n2dn/zI5jqoK4aYVDCEyLGESc4cOoPPLoSGMrj1\nd78PpSjKJiHEeLfbdUvDXlMIrwyG2f9ymIygCXsXS+VKTGqnTPetHPxV3piZszpluHd+O0irSXC3\nBt2N/l9QvBu+vxdmPQ9pE7r6bI5NmuvA1CIdos5g/8/wxaVw01JIdWvztOfwbzLOP/A0vw+l1rB3\nz1BMZDKc/66UOPmL+dfBls/8Y9R3fQ0vpEuvsD0rX4U/XtF+TCfcPm1A9zHqTdXwyTlweEXXnUNw\nBOiDpUfYXWmogB8f6ZB6rxkhkR2NuhCw+EHY/qX24yUPh/P/DfE2Tbi3zoXf/qn9WJXZMO9qyLOR\n2Pab1ilG3RO6p2HX6WD0lUeVEVojBNy8HE74s4ypfXMnbJun3fFj+8DISx17NBe+B1fM1W6s44nG\nKukNttrXx+HAr/CfGdoudO/4Ct4+4egirYW4dLjue+hzonZjdTaKDvI3QpQf1CP5m2V8u7ldX15F\nkXkH5Q6cGV+J6Q2jr7D/PeWuhf0/aj+WsUE6ZEabCrOtzVC4zT9CCy/pJkFVB1TnQ12Rf/TLiiLl\nWhaKd0ljrBW9xzk/7xjHHXcCII3qLcs7vm8IljOr5hrtpv9hsVKXHNR1hZz8Rlgs3PjL0XUKLcle\nDb/+FSbc2PGz21Z1fE8LaouhsVJeL8vfdPZr/vn7egyBO9bav1d+EN6bChd/KEsMHAN0zxg7yJT8\nA7/Cg/u0OSlbmmtl3C7tBFnwpzMpPyTHHnM1hHrWi/WYwmwCFP8tmHUlC2+RIZmzX+3qM/Gc/Utk\n9nbiQOlpbv4UkgbLei5a0VwLIZ1Yw3/5P2DFC/BUZdfcb8ZGOLBE2ouoFL8OdXzH2EGGSS76wD/H\nrimABTdC7jr323rDjw/DK04yRIt2wM+PQpWfNLj+xGySoSsh4Nu7ZNq/lvz6jCzL2tVEpUCkf3/A\nfsFslg7R8r/L/9cZYMU/Yc+32o7jzKgf+FWWaWhR3yhHFcMugIs/sjfqdSXyXsnSeJZw5Hf44nJ7\nuWNQGAw9z+9G3RO6bygmZYT/jh2XIVOEI9sSSnLWyYSH89+R4QBfyZgCYU5CBgNnwV+OHHOZbKrY\n9TX8/hJc8600GsZG9/t4gs4Aeie37MJb5A/Mg1o7LlnyJOSuhxt/7vjZac9qM0Zno9PBrSuOXhed\nXt7nWqpX1rwtDZyjkISxHmoL5SK4lqKEHoPlyxZFD0dWwMCZ2o0D0FIPNflAuzBP2UForIC0idqO\n5yXd17C31MviT4mDIErjjD5DiH3dB30QmI0dF4S8ZcjZ8uWI4PDOlVdqSUiU/N4ie8C5b2h//FMf\nd/5ZdO+jSUtakDDgmCvspAnt6ytpLUncMkc6XY4M+9Dz5Etryg/JpD/b32xEAty/W/uxBp0pX+1Z\n9qxci7vLTwXpPKT7xthL98vElAs/gJGXaHNiFiqz5SLQoDP84zmbTc7rUwshvZ6UEdDvFO3H7mxq\nCju3dkdnsHMh/PIU3PKbqpo+xwybP5Pna2uYjI2yGmK/aUfL7PqKqdX5zMofzPsTlO2HO/wUOlVD\n8S6p3e81xq/DHP8x9rh0uPY7/2jZ8zbI6nTtpW5a8eHpMMdJSQRFkaVo9/3gn7H9RV1pRxniqjfg\n1WFSseArDRVSfrhb43iwN0SlyEJt3c2jX/0mbG8n2zWEwoFfpNerFc6MutksY+ybPtFuLIAp98Ps\nlzq+/8er8IPGNaU2fQKfO3Akk4f53ah7QvcNxRhCoO9U/xx70Gy4ewtE20gPf/iLNFBa1AkZfZVr\nGd19OztXVaAFv/5VJg7dt/OozGzATJnMo2jgP5hapJLDWZXA7NWw4Ca4/HNtfmAfnSXzJByFlNIn\ny1d347bVUhJqi6LAPdu0kQbWFEpjOu5aaejao9NJ/bepxfexbHF2vevLoLbA8WfeYmpxvHbUUAE5\na2V+Q2dl3Lqg+xp2kItbJiNkeNbc2i3B4fZZbADhCXLxTgvGX+/68+4ocxx5mTR2tgYieah8aUFU\niut6PZHJ0PcUMGikO884Wfu1m65Gb3BsdLTSe9cVwfb/yXIYjgw7yOQurSnYAsFRkDjA/v3Tn9d+\nrIk3Oy5jUrIH/ncF/Olr/2bEq6T7xthBFugSAm7QOMMsf5OMmY35k3+SHFoapMfu7Nj7l8hMtlMe\n0n7szqa5Fkr3dU0ND39haoXXR8GEG2DKA119NurI+kOWzj35fpnyb0vpPvjxLzDzGeg1umvOzxfe\nHC8TCi/5uOvOobkOyvZJMUf771dDOiXGrijKJYqi7FIUxawoSuf/cs9+FS54V/vj7vkOvr/fP0Zd\nCNmMe9lzzrfJ+h3Wvi237Q5U58syt2Zzx89WvgwfnuG79HH9f+CtCe6P0xnfmd4gF9YTj52OOW7J\n3ywX5Q0OGqoYQmS5hpY6/5/Hhg/gv6dre8zz33H8gC3aIWsLFe3QbqwlT8K3d3d8PyRSZpP70ah7\ngq/Bz53AhYD/61U6ImmQ1JxrzZQH4Z6t9u8V7ZBe2hEf/1QhYMaT0H+G821m/FVq2btLX8zNn8Db\nE6HVgdEddSVcOc/3MFZUiqxX70rS+On5skCTr5jN8I8+sMqFJv6sl51LVo9FTrobHs13XMo2LkPq\n2z3o5eqQfT9Kh8hVk/GgcKk0M7X6NpYtaRMd57Xog+WCvrFJu7F0eueKtoNLtU+I8hKffm1CiD1A\n1zXmrcqRX+TQ87TVfodEdnzyhidCr7EyldwXdDo4+T7X23RWHWmtGHW5jKk6+m6SMuXLV4ac416O\nN/A0xx6ppwiTrO3ew0mc2Lqd6D4PX/C/BLHsAOz93nXbwNFXypeWHFouF7rb13NKGgQ3LtF2rJlP\nO//sl6cgJk37NT8v0CTGrijKb8CDQghVgXPNYuw7vpKp/7ev65h55gv7fpSr9/4o6GNqlVPekCjn\nT/7KLFj3vlxkTewmJXVdUbhdJpSlT+rqM9GOb++GvI1w++quPhP3CAGLbpf3s7NMzNVvyvv++m4m\nszW1wnMJMP1x/7fLdEf5IQiJhsgkvw2hWYxdUZRfFUXZ6eDlUQqZoii3KIqyUVGUjaWlpZ7s6pyB\np8Fdm7Uv37vhv/JGd4SvD8KS3fDPdNc69aZq2PSx/3o2aomlYJorrfrPj8ESF1mjavhgJvygYjHZ\nbHIc69eajJNh+AX+H0cLGivl4qmr+kOhMVJZ5G9tfnUevDMZ9mikjlEUuP4nqcpyxIKb4Je/ajMW\nyDoxK150/FlCf78adU9wOzcTQmhSbEEI8T7wPkiPXYtjEhrjn+7nl37SMdkGYOGtUJ3rm1cTmSy7\n7yQPd75Nykh4XGP9rb8o3Ca711y9QOrWHXHmP30PYfWd2rFHbHv2fAdfXgO3r7VPL/eU4l3wn1Nl\nYanBsx1vM/JS74/f2YTHw31uFhDHXiNfvrDsefl7nHyn821ComRM39f7wYJO73omGByp3VggSx47\nO17pflmfZtx1XR5O7d46drMZts2VP2It5XTBEY4vXtpE3+PFUcmub3zoXnHbXmPghp9lnWpnONM0\ne8KMp9xvkzRYqiOCfVQmhMbCxFtkeVtXWGYG/iwV++Mjsg7K7JeO/fuieKfM93BFaAxc8YV2YzbX\nQvYaKdOM7NHx83Ne024sgAv+7fyz7FXww4OyZEMX91XwVe54gaIoecAkYLGiKA5K4fkRnU5+kbu+\n1va4Gz903PV+wo2+65Zb6mVGnLtwwa/PwFYNfwD+IjhCZtu5mjkZG2VLNG+7xqsNfyUOhFOfkB11\nfCGmN8x6zvXDat9PMrZbvNO3sVwhhEzwqsrxrTvP+v/Ad/e43sZsliGSFQ5S89VyxVw47y3v9/eG\niiPwxSX+K7HtCcMvhAf2QVQv99v6GZ8MuxDiayFEqhAiRAiRLITQWKCqgjvWy4UTLVnxEuxe5Pgz\nIXyL4e6YDy/1d5/qfGiZDHMc6+z+1r7/ozMW3uJ9nZf8TfD33up6nZpa5cPTF8xm9w+TxIEy2cef\n5ZUVRYZHrvpSViv0lrpiaQBdodPJGak/5MPtWXAzfHmtNsdK6A83LYN0J0qUrV/Am+Mch1Y9xdgI\n70xy7nCFxkhZ7jHQXKZ7h2LAPx2O7t4CwoHxPrIS5lwoi4952/My7UQ48yX3U9Zbu7Bhsyf88BAM\nmAGpLloUBoXBnRu8by8YFicNnJpr/fIgGHa+a8mdO3Z+BV//WZ6zs4X5hP4yH8GflOwFUzP0HCUN\nk7dSzlOfULedL2GL5lq5BjXhBudrLRZ6DNFukTY4wvW9F54gNe7GRt+lsGaTvO7OZqfGRlm2OHV8\nlxcE6/6G/dByOVUdp5EHABDkJAkmLkN2borwYeXbUVOAriR3g4xNettA5NYVrhNSLPgi20zoD2f8\nQ922pzwMCf3cb+eKpEFw8r3uizmZWmWdfn/1RV31mkyIm/GU7Eh1327/qy4sMxVP4/kt9VJ106wi\ne3XK/Z6flzOq86Bgqyxx7ahwXubp8qUFIZGu6xWhyNDw9Ce63LAjhOj017hx44RmfHOXEC8O0O54\nxmYhlv9DiNwN2h3TlrpSIWqK3G+3fb4Q39zpn3OwUHZQiL9GC7HoDv+OI4QQhduF+O1FIUytnu/b\natT+fHzFbBbiuR5CLHnKf2OU7BUiZ50QRTuFWPKkEDWFnh+jMkeI/54hxJE/3G+75XMhnksWoq7M\n83G6iq3/k/dw6YGuPhNJbYl397hKgI1ChY3t+mCQr8x6TpYd1YrmWvjtHzKu6wiz2bcY7rLn4N8q\nUrersmX1Sn/WPonvJ0u5elsFL3e9XGhWE7/M3wzL/9bWVsxDfngQXlXZCtHUat+P0htMRvfrKIoi\n13b8WckvaZCMeycPk+34vOmpablX9cHut00cBONvcByG1JJdX8ML6VCV6/uxMk+HW393HqZrqIA3\nxsgQia8Ubpfx+mwXSWmRSc4TDzuR7h+K0VrHHpEAT1U4v7nfmwrxGW6mZC4YdaXseeqOKQ/4v3Kg\nohyVInqTHr/nO6m4GKsiDDbiYvnyRlM8YIb6Rb3fX5QJJE+Weq8lXvY3WPsuPOmm0cpJDopBacmR\n32XeQ9Ig+aCpLfBcRtdjsPrqp6njXMerXXHwV5ktfd5bjmWHtsSmy3tBizLYYbHy5YyQaBkW0aL5\nuCFU5pi4sjl7vpOqN3eluf1M9zfsFUdkaYExV3Xs5+gtOj3g5Kk78Wbf6qX3OQE4wfv9tWTzp3Jx\nqeyAzAe4fa1nxn3mMzDpDnUeii9JIp60bMs8A6J6+uZ19p/u2lhYMBmhqcY3xYorFtwss6vPewuW\nPgPr/g2P5vk3+UUIaG3yfN2gpUE2qlZzbr3HypcWFO2Q9++wCxzfu3oDXPyhNmMlZcIlH7neZudC\nKYHtYsPeveuxg0yV/vgsqVTRoqNSZbY0eGOu6thsQwsqs2QzCHdNHMoOwNJnYepD0HOk9ucBsgxu\n8jBZRO3wCrlA6a+FQJClGgwhMMbDCozNdfLBcKwl6Cy8VU7L3WV1ekvBVrkgmND/aI+AEZc6X9x3\nxKLbZRhGreLl7ROlikSLTmHu0KKI2q9Pw+q34KkyTU7JZ1oapGfvJ8nj8d/z1ELaifBEiXZt8qpy\n4I9XZJsvRwgh+3t6K9f68hqpcHCHMMsGCE1V3o2jhtvWwLlvSm/nnNc8M+rNdbKanSe1rnd8Jaeq\nniAEvNhX/oDVYDZLpYQvCT3NderWDUZd5t/CU71GH5Vb9h4nJZ+eGHWQzas9abg94UYYfJZnY3iK\n2QT/zIDfXvD9WJPvhtvclMpddLtsyuMrO76C10Y6tw0gq8wGdOwaoDeg6Z/Rd4qMsTtj6+fwzR1y\nwdabZI5Tn1Knp00aBHeu9/z4nqA3gN5GItZUoz7MVJUj49C9xzuuhe2IaxZ5riU2m+DUJ9VP3Rsr\nZAPtM/4JJ/7Zs7EsfHU91JfCLb+53s6fC6fGRhm37jXmaFy9rlSelyftBk971rNxHbV9U8PSZ6Gh\nHM5xUcPegk4v12W0KAMSHu9elpo63n2dITVE9pD5K65KhJfsle0BT7yjSwuCdX/DDrDyFVknxFnB\nJk9xNT1MOxHOfFEuyniDs7KpnU1NgQyNjL5SeoU//EV60/fvVjc9Th4KjxUCHoTyvEkQ0Rs8W6QM\nT4CzX/Ot2fSYq9U1ZzAZZVZnRJI2deBtqS2UTUPOf/do/fIFN8oZ3K1+7GsjhJzthEZ7FssXZs9m\nsac94/m5OeLwb/JaDTrD+Tbjb9BmrL5T3UcGqnJkZdgh53ZtpUc1mkitX5rq2IUQ4uUhQnz/gDbH\nyl4jxM9PCNFUo83x2lO4XWrZ1fD1bUKsetM/55GzToinY4U4uFT+//5fhFj9ln8145XZQnx7txCF\nO9Tv01wvREOF1I0fa+z7WWqoc9Zrf2xjkxAF2+w15Vmr5f2plv1LhHh1hNTDq2XPYvk35W9Wv4+3\nGJt9P8bnlwrx7snutzObO+ceMrUKYTL57fD8v9GxA9yzHc76lzbHKt4J69937X3UlcqXp5hNUsO+\nXuXCVGOl1NX7g7SJ8GQ59J0m/3/gTKlwUdtl54/X1P8dFoQZdi2SXo1a9v0g47Gl+9TvU1ssp8Te\nUl+urkdrygg5O/BHWYZrTpUAACAASURBVAtDiFw0t1XcpE/yrJRFaAykTvAsU7rnKDj971Jm6U++\nuwfe1EAZc97bsviYK/b9BM/3lL0QfGHZ32TjbFfo9MdEjL37q2K6gn/0kQtnsz2shGc2yS41CQOO\nrbICFloa5MKjmtLEn10op+uedIb3Jl29dD8cWCJrXKttFDz/Ormoe5eK4mSOeHmIjJ+f/7Z3+2tB\nZbZUwgyYeXTdQwjIWSu/B7XrGp3FBzNh9FXqZX57f4Dyg/7PBQB5D235VJZi9rZeEcDOBbIEx5ku\nFn2FkNLU3uP90hNXrSrm+Iix7/ke8je67keoJbNf8k4KqdMfOw2QD/8m6+xMf+xofPjrW6BoZ8dG\n3o7400LPs2K9kbZ50zP1xDugxYeZzqmPq08EqsoBfYh7+aqnZK+CRbfB3VvtF7TnXS2zLc9/x/0x\nzGbvvMfGKmiuUW8ETUYIi/dMVaXVetiOr+SMpN8pzrdJyoRZf/N9rOEXuW+XqSiwbZ78dxf+1o8P\nj/2Xv8p632oX/lyxfT6U7VNfEc8TWupliCBxgLqM2Q0fSM/mTwu1P5c/XoXl/4DHC48mGGWvllK/\ngaf5TzO+ZY7MPXDVsMCWmkL54HGnfOgqnu8lZxNn/F3b4zbVyNlT4kD7RczcDVKNpWZh7vXRUrro\nacmID89saznn5/6nLfWgCwKDinIHznhtpAxPXfi+6+2EkA8gX8ZSix+bnP//0bGD9NQf2KPNl5m3\nwX0/xsYqz/TbFkr3wgenyo4vqlAA4Z96MSffB08U22eNpk+GzFnuv8dDy+GrG71bZ6gvlVNwtTXt\nF90Gn1/i2RjNdZCzTvaO9RSzWdYwaWlQt/25b/inTV5otFQetVempE1QZ9SFkN5l6gTPx57ygLYV\nGB2R9Qf8vRfkqP0tOOHmZXCGCj38i/3U50I4Y+6VMOdi99sdC4l0alZYtX5prorpbJa/IJUDxibP\n9muoFGLfT7IC3LFKyT4hsla53mbbPCFeGS5ES4P/z2f/L1Kp4QlHVsrrc3CZ5+M1VMh9V7/t+b5a\nkr1WiJ0LO77fVCPEpk88U7r4m6xVQrwzWVahVEtNkRArXxGi/LD/zsuW31+WKiZfWPueuvti+3wh\nfnzUt7GcgEpVzPERY684DKtel7XSXbUz04qh57UVz/LwyRwWq11taF9Z+29AwIm32b//86NQnQ93\nrHW+78hLO6+Zsze6/+ThcNVXUuHhKYZQOOcN9Z5ubZFMzNGir6stWz6TCUrDLrB/32SUmcszn3Hd\nsLulQYawvKk0aGyS4cjYdHU1c/TBcltPes1GJctZoy8IIZPk+pzoPoFNixnICbeo265kt7x2aBye\n8wQ11l/rl+Yee+EOWZP9wK++H2vFi0Ks/bfvx3FEdYHUIav19At3CPHeNP/opL+4XIg5lzges/yQ\n9uNZMLXKcTf81/22rUYhinYJ0VTrv/Pxla9vF+Jfg7U/bkOFEBVHHH9Wfsi9Vnr5C7K2uqezSiGE\nyNsoZy27v/N8X09oqhGivtz7/Zvr5XmufMX9tmazEI1V3o91jMD/Kx17ynB46IAs7+orOeuc12K3\nYGqFgi3Ss/WEfYvhw9NljF4NQWGyLZw/YnZXzJW9NNuTMty14qeuFN6fLnuyeoNOL7sOmVrdb1tb\nCO9OkjIzT8nb5F3PWGOjnAGqyTwFmHgTnPem5+O4IyzOecmK+H7u1S7pk2HqA95lxCYOgks+8S4+\n7wnvTIafHvV+/6AweDhbyhjd8ePDcqHVF14dDj8+4tsxOonjIxSjJVd/5X6b1kZ4f5pctPVkOjlo\ntqxZoVbhkdDfP4oYd+z7CcytjuVaTdWy0qLBhyqQf/pa3XZhsXDxR961GfvmdpkvcPnnnu2Xvxk+\nng3XfOtaQmfBXy3Qdi6QEsL+0zt+VnEYNn0MJ9wG0T0d7993inx5Q0ik7BurlqXPQtYquPFnz8Y5\n9XHfEqEURV2oCOS9HN/XN8XKmKuhh4o6PWUHYcULcNK90lHqAo4fw/7z49LD8baIkSeERMHlcz2P\nq0b30q5mvC8IAd/cKW/2QWd2/HzNW7K6oSPDnjgArnOjGtKKkCgYfqF3+57/DoSq/NHbkjBA1mdJ\nUplA1lQNJXvkveCo56a3LP+7TEJyZNgbq2DNO9BvmmPDbjbL2U50L++NWPkhqCuR2a7uiO0DKTWe\njzHqcs/3saWuVBblG3KO86bjFtTUeXHHNJXeurlVqusaurCUsJp4jdYvv6hiPjpLiB8f8f04i253\nrEbQgqJdst6HJ3xyrhBL/6bteRibhHhlmPMV/qo857FZLept7PtZiDcnyDUHV1TmyJi/H2tv+Mz+\nX2ScN3uttsetL3fee9TUKkRLo/N9yw/Jc9r0iffjz79e1pnxJ811su+ut1jWAvb+6H5bk0l+n94q\nuTqr1owb+H8VYwfpRartZO8M0ZayraaWSfkh2brME9a+DV95WGkuLsN9qzFPMYTAfTth0u2OP4/p\n7Tg2a2qVJXHXuUkGcUdYnEy8aXUTx974IbyvIhziiMps2c3G07r59eUyBV3NGgBINcZVCzzPjnVH\neLzzzkw6veu67KGxcNYrvnmoUx6ESz/1fn81rH5T9hA1Gb3bv9dYeKxA3dpa0XZ4qZ/3a0P1ZfBM\nnKyI2h1QY/21fnV7HbsQQnxzp1TieEL5ISFyN/jnfLRm8xwhfn3W/r2GSiG+u1d6qZ1B6QEh9v7g\n3b7r3pfeXE2hZ/uteVfu54taw1daW4RY9Yas7uiMnPVCfH6ZvCZdzTsnCfHL057vV7hd5kRoUeXR\nHQ2VUu3mreKrsUrOnPM2qtv++weE+OM178ZyAf/vPPYdX8k6Gp3F5Lsdq0pcEd9Pm+YCvlKyFxbc\n5LpiYuE2OSOxzRANi4WzX+28mvKJAxyvAahh6Plw22pZn90TBp4GF/3Xs3r72aull68VjVWw5AnI\nXed8G1OL1JpX53b8rHCbbx2kQOrg9/0oWzm6o+8U9WsStqSMkPkQ3qb5F++CFS+p+1vDYuGEW71v\ndxkaIxd7e6ts9l1TILOsu4jjx7A3VckQSmuL98eoLZKt69Sk/CcO9FwRkfWHVF14wu8vSVmYljRW\nQt5G16VpT/873PTLUVmdEDK8oRVf3ShTtF2RvVqdYXFEZJJc0PS08XNCfxhxsfryxQCfXyrDRloR\nkQiP5Mpqic5Inwx3b+lY5dFshk/PhyVP+nYOzTUw93LYv8T9tmf8Q1Y79RSTUToX3j6ECrbC8r/J\nc1VDfZk0uN5gNnkWMrriC20Kj3nJ8WPYJ9wkO8v4UuTHUqSrpc79tk01sHexZzfKDw/B7x7WjY/N\nkF6+0LBeTPokWcGx12jn21gMW0OFVMhkrYTXR8IulVJFd/QaDaluvJ+5V8g4rDeYjFIy6GlNn4oj\nntV+Bzlza5/B6wuKImvFuGrBZlG7CAe1hC79RH2WpDMik+Gmpd4ZbLXUFsLbE+XvyBvGXAVPlkGM\nyiqUn5wLix/0bqwjv8NzidLZ6A6oiddo/TouYuwle2UsdtuXHuyzT8aNuwt1ZUK82F/GFhsqhfjj\ndddqDC0xm2Uc2duaKK1G2SFq6XOe7ffVjUK8Nsq7MbWi7KCsbeJufSBvoxCvjRSiYGvnnJcjslYL\n8Y80z9VeQsjY+vb5QlRkaX9ejtizWIjDK7zbt/yQEL+9KER1vrrtt8+XSj2NFV38v4uxV2bDnIvg\nyMrOGS+ur2x27KrXYnuSMmXcuKvZuVA2o3Cn/IhIgHHXyyqBYbGyKYIrNYanmM3Op7eKIisZuqqH\n4gq9AW5fByfd49l+k+6Es1/xbJ/iXW21QTSieJds1uAuRhubIXX3ZpvruPULqdjSgoItsNVNd6Lw\neBh5mXf5GYZgGfaKS/fu/A4ulaWn1TJ4tvdKofh+cMpD6v9Os0l2DDOqrBKqMT4ZdkVRXlIUZa+i\nKNsVRflaURQvMkI0Qh8sizG1Nnt/jJy1Mu6rRu5oCJYxdrVJKWaTXOD19EeXtxFeGigz+7SioVyG\nnNQUiDr1cf90e6rKhX+mw475jj+vzJLxXTUt6pyRlOl50lCv0bJ7kiesfRcW3eHZPq4Yco5sFO4u\nyzEiAa5ecHRBr7kOvr9fGnct2LlQtrBzVWI5aZBsPOOtcS4/JB9k3pC10rNQXVM1FG73LqxpbJL3\notp9R10m69mr7fqlMb567L8Aw4UQI4H9gA+FH3wkuqf0oH1RbDTXQVW2+ot35HfYrzKNuqladpk/\noGIxypaIJKkMCYvzbD9XTLxZVm/syrrR0b1g1BXS43TEvp/gi0vkuoe3ZK+BLR6WFCjYIlP2PWHK\nA3DNIs/2cYWiyPi62sqMTTWw+1tpRO7cAOM9zJVwxuS74b5dru8TT/ME2vPdPbD4Ae/2nfk0PJqn\nfvstc+C9KVJo4SkbPoDnU9Qv1HYxmnVQUhTlAuBiIYSLpXxJt+95amHORXKl/dYV7rc1tUqDER4v\nVQ8BXNNYKSWEaRO9fwAtfkAuoD6cpX6fN8bImdjFGqpcPOXQMlmIbsqD6v72JU/K1PoHD3Z+I+VF\nd0DeevlA8Ybc9aDo3S+ka0H5IVlSd8BMz9r4gbweR36HSXepU0zVFsP8a+XDUas2gHRNz9MbgHka\nHs9zvr1LZt3Neq5zxjv7NVm/Ww16g/bZid6y9FkZ2+6s78kVtcVyVtLeIIXFQZ8TfDv29Mc9b3F4\n/rsQ5EKN4ojaIill7X+qNi38Di2DjR/D1IfUbX/qE7LAldZGvbUZNn8KPUfL9Q5HDJzp232dNtH7\nfTd/JhVsahVJCf3d15RxRu9x6jXsIB8cOgMoXbOM6XZURVF+VRRlp4PXeTbbPA60Ak7nvYqi3KIo\nykZFUTaWlvpJuK8zyJe3bJkjNclqZzGxaeralIHsX7ltnnea3TfHwQ9/8Xw/ZzRWSY+4q9k2D17O\ndBz62PY/79oP2hIe73kIq8+J0NPD8q7Fu2SYzVOZpDNm/Q0ePqJ+e0OIduEXW3T/1955h0dVpX/8\ncxKSAElASpBOwEVAeiiisFQFJdiQXUVULCgi61oWbOwq2Av6w7YquHZUXFRAxQVRmlhBEZFQpaOk\n0EIIkGTO7493EpIw5bZMZib38zzzZObOnXvPyb3zzjnved/vW00SpdYHEH1rf4n5BerSHM6SHzIr\na2ObFsKvJlxgRQXiajv0u/lzHT0oLi+jVK8lMidmgiucxEjoTKAHMBr4Bqhp9DNhG+743XStXxls\nfP/926Vclj+xptL8OlfCI39fY75dXz6s9S8fmP9cuLNvqwiRlS8VWHhc6yl1raWpl+bQH5KabzSN\nvKhQyukd2GXuPEcPab03I3ShoKEkd29g8Su7RVB+eke+FxVZ3KWYI/u9ZQ+fN//ZD28S4bxKBoPh\njrZ87Eqp84CngX5aa8PD8KjxsW/5Et66BK6ZD6m9A+97/IgkZNRuaq34QVVCazi8F1BSQs0qmRnw\n717iL+9wafD98/fD46kw5FH/Ammh4PsZ4uJLu6ry2mCE43lSkPrcB6yP2nP3SnHzxl0DJ2Q5gdaw\nYb5k655iMKmpmC2LJRmxa9AlxBN8fKvMRC55ydy5AmDUx27XAfQ8kAx8rpRarZRyrgdWWPO+pN/b\nCXk0Q/OzYMIm+RuM+Jri37Nq1O1GH5TmreGw6g3njmeH40dgZ7mFN6UguaE9ow5QrzXcvQPaG9R0\nj0uEaz+DMy40dx6t5d7b5dBg5dePIONjZ45ll73rpNaBL9ed1lJ7NbWP9eMnnyqDIitG/YsHJYTY\nKEpB23TzRh1EF9+MUQfJ3rVTSMQGthZPtdZhkG1TioRkWUQqyLdmQBf+S0YhRhNU4moYX13f8R3s\n2wJdguij+OJ/98gNPHGT+c+WR2sRkNIO/lDY4evnYMmjErlSXA0n4xM4lgtdRto7dmw1iK1tfP9q\n8aLBYhalJFW98+XOiLxdO99ZCQk7HNojoX4dLoUm5dYrEpKgz232ju8pgt8WiyyA2UXYjI8lAajj\nCOOfydogvnJ/i8H+yN0rNsVoxSaAAfeaO4eDRE8FJZB4b6tqgABY+DL9+KYoCLZND7zf2g9kQdCK\nYW/ZT8qkOYFSoauAZISOI2QaXvoH8qe3xG1l17CDLIirWGPHysuBPT+KcTa76Dp2qXklyUBUZo5B\naVr1F81zXzH1+Qdku93KUTP/Cn++w3wE09++N3+uLx4QPaCbTWq+zBwBtZrAFe+ZP2cl4Fgcuxmi\nxscO8EIvkQm47O3A+x07LIkRtZuGpl2RjMcD+fucifd/LV1G7lfPDb7v5kWSm3DdQvuhllbRWgov\nnz5Y4q3DmUVTYMUz8K8s48lUvti1UtwjTheU8cUfayXV32zk07p54i4yc03WzYOFk+R+8leb1iSh\n8rGHF7l74fme5vxudrl+AfzFQKWZhCR7Rr3wuPGqPoHI3gSvnCPyCeFC7l5Jyy+WXI6JcS6J66oP\n4SqDIXFNe8D1i+BUAwWLy7N1mfksV18UHReZBatp9hXBz7PgMx/1Ptumw3mP2TPqIDMks0b9WC7M\nHS/5A2Zo2MG8UQdZdzH7Q5vUAJr1wpInwCbRZdgTksVPZ8YPVpq3R8gIxAzVaxtLDPl5Fmz63Fq7\nti6Dh1ICF14wivZAfKJ5nfKK5I9f4H93S/8WPwrLTYpwBaJagnG3RvXa4nu14lr4ZTYsmmz+c+Wp\nliAx7HZiw50mewNsX3GyZkzT7vblgUFqFKyfb+4zxw7D5i/N66sfzhSZ4GO55j6Xs0Vi2c3QvBdc\nOqNSCthHl2GPrykuEatT2PhE45mkxfyxVhZd84PoTyx7QtK+rVD3NBjwT2dukJQ24pYwk0VX0Zw2\nUKodpfaB7I1waLdzx97zk4w2jXwp964TA2PFPXnOZLglStyL5Rn4L7hpedkBjKdIZhVORKD98B+Y\nb1InvVYj+EeGVGAyw66V8N4VEmJpFI8HnkuDb14wd65KxPWx22X9p/Dfa+GGL2Wa54/jR6DomLNi\nXtGIxwOF+fIj6wS/fgRz/yYCcfVbB9738/vEJfTPzMpbvMzZAl8/C73Gh48EhS+yN8Pz3eCiF6Cr\nzZKUB3ZKlFadVEeaFpD8/bJ4mtLWeIilp0iCH1LamnPjFBXAs2kiutf779baW46q6WMHKbn2nsl4\nUzu0HgKT/ghs1EFuIjtGvSDfXEqzP9a8D9P7B59hVBYxMc4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ExT8ZH8NTbZ0pNRkMpeQe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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24da6a78c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Par MSE = 0.0478330206665284\n",
      "Seq MSE = 5.0095899766664\n"
     ]
    }
   ],
   "source": [
    "plt.plot(prediction, label=\"parallel prediction\")\n",
    "plt.plot(sequential_prediction, label=\"sequentiel prediction\", ls=\":\")\n",
    "plt.plot(outputDataValidation, label=\"groundtrouth\", ls=\"--\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.plot(prediction - outputDataValidation, label=\"diff parallel prediction\")\n",
    "plt.plot(sequential_prediction - outputDataValidation, label=\"diff sequentiel prediction\", ls=\":\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "print(\"Par MSE = {0}\".format(np.mean((outputDataValidation - prediction)**2)))\n",
    "print(\"Seq MSE = {0}\".format(np.mean((outputDataValidation - sequential_prediction)**2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:51:21.876105Z",
     "start_time": "2018-02-18T20:51:21.705943Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100% (1 of 1) |###########################| Elapsed Time: 0:00:00 Time: 0:00:00\n"
     ]
    }
   ],
   "source": [
    "esn = PredictionESN(n_input=1, n_output=1, n_reservoir=50, leakingRate=0.2, regressionParameters=[1e-2], solver=\"lsqr\", feedback=False)\n",
    "esn.fit(inputDataTraining, outputDataTraining, transientTime=\"Auto\", verbose=1)\n",
    "sequential_prediction = esn.predict(inputDataValidation[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-02-18T20:54:32.304914Z",
     "start_time": "2018-02-18T20:54:32.301899Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(reservoirs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
